Qbd: Quality by Design in Pharmaceutical Product Development

Quality by design (QbD) is a concept first outlined by quality expert Joseph M. Juran in publications, most notably Juran on Quality by Design.

Designing for quality and innovation is one of the three universal processes of the Juran Trilogy, in which Juran describes what is required to achieve breakthroughs in new products, services, and processes.

Juran believed that quality could be planned, and that most quality crises and problems relate to the way in which quality was planned.

While quality by design principles have been used to advance product and process quality in industry, and particularly the automotive industry, they have also been adopted by the U.S. Food and Drug Administration (FDA) for the discovery, development, and manufacture of drugs

Quality Target Product Profile that Identifies the Critical Quality Attributes of the Drug Product

QTPP is a prospective summary of the quality characteristics of a drug product that ideally will be achieved to ensure the desired quality, taking into account safety and efficacy of the drug product. QTPP forms the basis of design for the development of the product. Considerations for inclusion in the QTPP could include the following (3):

• Intended use in a clinical setting, route of administration, dosage form, and delivery system(s)

• Dosage strength(s)

• Container closure system

• Therapeutic moiety release or delivery and attributes affecting pharmacokinetic characteristics (e.g., dissolution and aerodynamic performance) appropriate to the drug product dosage form being developed

• Drug product quality criteria (e.g., sterility, purity, stability, and drug release) appropriate for the intended marketed product

It seems obvious that a new product should be adequately defined before any development work commences. However, over the years, the value of predefining the target characteristics of the drug product is often underestimated.

Consequently, the lack of a well-defined QTPP has resulted in wasted time and valuable resources. the significance of defining the correct QTPP before conducting any development. Also, QbD examples exemplify the identification and use of QTPPs

It is the quality characteristics that the drug product should possess in order to reproducibly deliver the therapeutic benefit promised in the label. The QTTP guides formulation scientists to establish formulation strategies and keep the formulation effort focused and efficient. QTPP is related to identity, assay, dosage form, purity, stability in the label. For example, a typical QTPP of an immediate release solid oral dosage form would include

– Tablet Characteristics

– Identity

– Assay and Uniformity

– Purity/Impurity

– Stability, and

– Dissolution

It is important to acknowledge that QTPP should only include patient relevant product performance elements. For example, tablet density or hardness may be included as a specification for process monitoring but may not be included in QTPP. Also, if particle size is critical to the dissolution of a solid oral product, then the QTPP should include dissolution but not particle size

To design and develop a robust drug product that has the intended CQAs, a product development scientist must give serious consideration to the physical, chemical, and biological properties of the drug substance. Physical properties include physical description (particle size distribution and particle morphology), polymorphism and form transformation, aqueous solubility as a function of pH, intrinsic dissolution rate, hygroscopicity, and melting point(s). Pharmaceutical solid polymorphism, for example, has received much attention recently since it can impact solubility, dissolution, stability, and manufacturability. Chemical properties include pKa, chemical stability in solid state and in solution, as well as photolytic and oxidative stability. Biological properties include partition coefficient, membrane permeability, and bioavailability.

Pharmaceutical excipients are components of a drug product other than the active pharmaceutical ingredient.

Excipients can:

(1) aid in the processing of the dosage form during its manufacture;

(2) protect, support, or enhance stability, bioavailability, or patient acceptability;

(3) assist in product identification; or

(4) enhance any other attribute of the overall safety, effectiveness, or delivery of the drug during storage or use.

They are classified by the functions they perform in a pharmaceutical dosage form. Among 42 functional excipient categories listed in USP/NF, commonly used excipients include binders, disintegrants, fillers (diluents), lubricants, glidants (flow enhancers), compression aids, colors, sweeteners, preservatives, suspending/dispersing agents, pH modifiers/buffers, tonicity agents, film formers/coatings, flavors, and printing inks. The FDA’s inactive ingredients database lists the safety limits of excipients based on prior use in FDA-approved drug products.

It is well recognized that excipients can be a major source of variability. Despite the fact that excipients can alter the stability, manufacturability, and bioavailability of drug products, the general principles of excipient selection are not well-defined, and excipients are often selected ad hoc without systematic drug-excipient compatibility testing. To avoid costly material wastage and time delays, ICH Q8 (R2) recommends drug-excipient compatibility studies to facilitate the early prediction of compatibility. Systematic drug-excipient compatibility studies offer several advantages as follows: minimizing unexpected stability failures which usually lead to increased development time and cost, maximizing the stability of a formulation and hence the shelf life of the drug product, and enhancing the understanding of drug-excipient interactions that can help with root cause analysis should stability problems occur.

Formulation optimization studies are essential in developing a robust formulation that is not on the edge of failure. Without optimization studies, a formulation is more likely to be high risk because it is unknown whether any changes in the formulation itself or in the raw material properties would significantly impact the quality and performance of the drug product, as shown in recent examples. Formulation optimization studies provide important information on the following:

• Robustness of the formulation including establishing functional relationships between CQAs and CMAs

• Identification of CMAs of drug substance, excipients, and in-process materials

• Development of control strategies for drug substance and excipients

In a QbD approach, it is not the number of optimization studies conducted but rather the relevance of the studies and the utility of the knowledge gained for designing a quality drug product that is paramount. As such, the QbD does not equal design of experiments (DoE), but the latter could be an important component of QbD.

Drug substance, excipients, and in-process materials may have many CMAs.

A CMA is a physical, chemical, biological, or microbiological property or characteristic of an input material that should be within an appropriate limit, range, or distribution to ensure the desired quality of that drug substance, excipient, or in-process material. For the purpose of this paper, CMAs are considered different from CQAs in that CQAs are for output materials including product intermediates and finished drug product while CMAs are for input materials including drug substance and excipients.

The CQA of an intermediate may become a CMA of that same intermediate for a downstream manufacturing step.

Since there are many attributes of the drug substance and excipients that could potentially impact the CQAs of the intermediates and finished drug product, it is unrealistic that a formulation scientist investigate all the identified material attributes during the formulation optimization studies. Therefore, a risk assessment would be valuable in prioritizing which material attributes warrant further study. The assessment should leverage common scientific knowledge and the formulator’s expertise. A material attribute is critical when a realistic change in that material attribute can have a significant impact on the quality of the output material. Product understanding includes the ability to link input CMAs to output CQAs.

The steps taken to gain product understanding may include the following:

1. Identify all possible known input material attributes that could impact the performance of the product

2. Use risk assessment and scientific knowledge to identify potentially high risk attributes

3. Establish levels or ranges of these potentially high-risk material attributes

4. Design and conduct experiments, using DoE when appropriate

5. Analyze the experimental data and, when possible, apply first principle models to determine if an attribute is critical

6. Develop a control strategy. For critical material attributes, define acceptable ranges. For noncritical material attributes, the acceptable range is the range investigated. When more than one excipient is involved, these defined acceptable ranges may be termed formulation design space

A pharmaceutical manufacturing process usually consists of a series of unit operations to produce the desired quality product. Unit operations may be executed in batch mode or in a continuous manufacturing process. A unit operation is a discrete activity that involves physical or chemical changes, such as mixing, milling, granulation, drying, compression, and coating. A process is generally considered well-understood when

(1) all critical sources of variability are identified and explained,

(2) variability is managed by the process, and

(3) product quality attributes can be accurately and reliably predicted .

Process parameters are referred to as the input operating parameters (e.g., speed and flow rate) or process state variables (e.g., temperature and pressure) of a process step or unit operation. A process parameter is critical when its variability has an impact on a critical quality attribute and therefore should be monitored or controlled to ensure the process produces the desired quality. Under this definition, the state of a process depends on its CPPs and the CMAs of the input materials. Table I lists the typical manufacturing unit operations, material attributes, process parameters, and quality attributes for solid oral dosage forms.

Process robustness is the ability of a process to deliver acceptable drug product quality and performance while tolerating variability in the process and material inputs. The effects of variations in process parameters and material attributes are investigated in process robustness studies. The analysis of these experiments identifies CPPs that could affect drug product quality and establishes limits for these CPPs (and CMAs) within which the quality of drug product is assured.

Steps to establish process understanding are very similar to those of product understanding and include the following:

1. Identify all possible known process parameters that could impact the performance of the process

2. Use risk assessment and scientific knowledge to identify potentially high-risk parameters

3. Establish levels or ranges of these potentially high-risk parameters

4. Design and conduct experiments, using DoE when appropriate

5. Analyze the experimental data and, when possible, determine scalability and apply first principle models to determine if a process parameter is critical. Link CMAs and CPPs to CQAs when possible.

6. Develop a control strategy. For critical parameters, define acceptable ranges. For noncritical parameters, the acceptable range is the range investigated. When more than one process parameter or material attribute is involved, these defined acceptable ranges may be termed process design space

While developing a strategy for investigating both product design and understanding and process design and understanding, studies can be designed in such a way that both the objectives of product and process understanding are achieved simultaneously. In addition, an interactive (or interdependent) relationship among material attributes, process parameters, and product attributes can be more easily developed when such analyses are performed in carefully planned and designed experimental studies.

QbD Risk Assessment is the backbone that links other QbD elements – design space and control strategy – together. In a QbD dossier, risk assessment section serves as the executive summary for regulatory reviewers. As such, Risk Assessment plays an essential role in the QbD framework

Quality risk management (QRM)
The FDA defines a Risk Management as, a strategic safety program designed to decrease product risk by using one or more interventions or tools. It is systematic process for the assessment, control, communication and review of risks to the quality of the drug product across the product lifecycle.

The ICH Q9 guideline: Quality Risk Management provides a structure to initiate and follow a risk management process.

Failure mode effects analysis (FMEA)
FMEA is one of the most commonly used risk-assessment tools in the pharmaceutical industry. It is a systematic and proactive method to identify and mitigate the possible failure in the process. Failure modes represent any errors or defects in a process, material, design, or equipment. Once failure modes are established, FMEA tool evaluates the effect of these failures and prioritizes them accordingly. This tool is further advanced with studying criticality of the consequences and providing clear indication of situation.

Failure Mode, Effects and Criticality Analysis (FMECA)
It is the extension of earlier said FMEA tool. Extending FEMA to incorporate an investigation of the degree of severity of consequences, their probabilities of occurrence and their detect-ability is Failure mode, effects and criticality analysis. In FMECA, each failure mode of the product is identified and then evaluated for criticality. This criticality is then translated into a risk, and if this level of risk is not acceptable, corrective action must be taken. This can be utilized for failure and risk associated with manufacturing processes. The tool can also be used to establish and optimize maintenance plans for repairable systems and/or contribute to control plans and other quality assurance procedures.

Fault tree analysis (FTA)
This tool assumes failure of the functionality of a product or process. The results are represented pictorially in the form of a tree of fault modes. This can be used to investigate complaints or deviation in order to fully understand their root cause and ensure that intended improvement will resolve the issues and not cause any other different problem.

Hazard analysis and critical control points (HACCP)
HACCP provides detailed documentation to show process or product understanding through identifying parameters to control and monitor. The definition of hazard includes both safety and quality concern in a process or product. It involves hazard analysis, determining critical control point, establishing critical limit, establishing a system to monitor critical control point and establishing a record keeping system. This might be used to identify and manage risk associated with physical, chemical and biological hazards.

The output of a risk assessment may be a combination of quantitative and qualitative estimation of risk. As part of FMEA, a risk score or Risk Priority Number (RPN) may be assigned to the deviation or to the stage of the process that is affected; this helps to categorize the deviation. RPN is calculated by multiplying Probability (P), Detectability (D) and Severity (S), which are individually categorized and scored. Rating scales usually range from 1 to 5.

RPN = probability score × severity score × detectability score

Where, the score was defined prior to the risk analysis stage. A RPN of < 40 was considered a low risk; a RPN of 40–99 was identified as an intermediate risk; and a RPN of ≥ 100 was defined as a high risk

Design space
ICH Q8(R2) defines design space as “ the multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality. Working within the design space is not considered as a change. Movement out of the design space is considered to be a change and would normally initiate a regulatory post approval change process. Design space is proposed by the applicant and is subject to regulatory assessment and approval.”

Design space may be constructed for a single unit operation, multiple unit operations, or for the entire process. Though according to FDA guideline, defining design space is optional since the product and process understanding can be established without a formal design space, nevertheless, such approach can assist to better understanding and attain overall control of a system.

The Design Space is linked to criticality through the results of risk assessment, which determines the associated CQAs and CPPs. It describes the multivariate functional relationships between CQAs and the CPPs that impact them, and should include their linkage to or across unit operations. Such relationships are arrived at by iterative application of risk assessment and experimental design, modeling, as well as the use of literature and prior experience.

Methods for determining design space included: one-variable-at-a-time experiments, statistically designed experiments, and modeling approaches. Methods for presenting design space included graphs (surface-response curves and contour plots), linear combination of parameter ranges, equations, and models. Alternatively, the design space can be explained mathematically through equations describing relationships between parameters for successful operation

Control Strategy
ICH Q10 defines a control strategy as “a planned set of controls derived from current product and process understanding that assures process performance and product quality. The controls can include parameters and attributes related to drug substance and drug product materials and components, facility and equipment operating conditions, in process controls, finished product specifications and the associated methods and frequency of monitoring and control.” A control strategy normally include input material controls, process controls and monitoring, design space around individual or multiple unit operations, and/or final product specifications used to ensure consistent quality. The finished drug products are tested for quality by assessing if they meet specifications. In addition, manufacturers are usually expected to conduct extensive in process tests, such as blend uniformity or tablet hardness.

A QbD based control strategy for blending process. Pharmaceutical quality is assured by understanding and controlling formulation and manufacturing variables to assure the quality of the finished product. The end product testing only confirms the quality of the product.